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#!/usr/bin/env python
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import sys
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import os
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import re
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import time
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from math import *
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from array import *
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from decimal import *
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from optparse import OptionParser
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from OSUT3Analysis.Configuration.configurationOptions import *
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from OSUT3Analysis.Configuration.processingUtilities import *
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from OSUT3Analysis.Configuration.formattingUtilities import *
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### parse the command-line options
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parser = OptionParser()
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parser = set_commandline_arguments(parser)
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parser.add_option("-f", "--fancy", action="store_true", dest="makeFancy", default=False,
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help="removes the title and replaces it with the official CMS plot heading")
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parser.add_option("--ylog", action="store_true", dest="setLogY", default=False,
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help="Set logarithmic scale on vertical axis on all plots")
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parser.add_option("--ymin", dest="setYMin",
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help="Minimum of y axis")
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parser.add_option("--ymax", dest="setYMax",
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help="Maximum of y axis")
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parser.add_option("-E", "--ratioRelErrMax", dest="ratioRelErrMax",
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help="maximum error used in rebinning the ratio histogram")
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(arguments, args) = parser.parse_args()
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if arguments.localConfig:
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sys.path.append(os.getcwd())
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exec("from " + arguments.localConfig.rstrip('.py') + " import *")
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#### deal with conflicting arguments
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if arguments.normalizeToData and arguments.normalizeToUnitArea:
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print "Conflicting normalizations requsted, will normalize to unit area"
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arguments.normalizeToData = False
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if arguments.normalizeToData and arguments.noStack:
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print "You have asked to scale non-stacked backgrounds to data. This is a very strange request. Will normalize to unit area instead"
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arguments.normalizeToData = False
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arguments.normalizeToUnitArea = True
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if arguments.makeRatioPlots and arguments.makeDiffPlots:
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print "You have requested both ratio and difference plots. Will make just ratio plots instead"
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arguments.makeRatioPlots = False
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if arguments.makeRatioPlots and arguments.noStack:
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print "You have asked to make a ratio plot and to not stack the backgrounds. This is a very strange request. Will skip making the ratio plot."
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arguments.makeRatioPlots = False
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if arguments.makeDiffPlots and arguments.noStack:
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print "You have asked to make a difference plot and to not stack the backgrounds. This is a very strange request. Will skip making the difference plot."
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arguments.makeDiffPlots = False
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from ROOT import TFile, gROOT, gStyle, gDirectory, TStyle, THStack, TH1F, TCanvas, TString, TLegend, TLegendEntry, THStack, TIter, TKey, TPaveLabel, gPad
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### setting ROOT options so our plots will look awesome and everyone will love us
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gROOT.SetBatch()
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gStyle.SetOptStat(0)
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gStyle.SetCanvasBorderMode(0)
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gStyle.SetPadBorderMode(0)
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gStyle.SetPadColor(0)
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gStyle.SetCanvasColor(0)
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gStyle.SetTextFont(42)
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gStyle.SetCanvasDefH(600)
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gStyle.SetCanvasDefW(600)
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gStyle.SetCanvasDefX(0)
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gStyle.SetCanvasDefY(0)
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gStyle.SetPadTopMargin(0.07)
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gStyle.SetPadBottomMargin(0.13)
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gStyle.SetPadLeftMargin(0.15)
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gStyle.SetPadRightMargin(0.05)
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gStyle.SetTitleColor(1, "XYZ")
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gStyle.SetTitleFont(42, "XYZ")
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gStyle.SetTitleSize(0.04, "XYZ")
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gStyle.SetTitleXOffset(1.1)
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gStyle.SetTitleYOffset(2)
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gStyle.SetTextAlign(12)
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gStyle.SetLabelColor(1, "XYZ")
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gStyle.SetLabelFont(42, "XYZ")
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gStyle.SetLabelOffset(0.007, "XYZ")
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gStyle.SetLabelSize(0.04, "XYZ")
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gStyle.SetAxisColor(1, "XYZ")
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gStyle.SetStripDecimals(True)
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gStyle.SetTickLength(0.03, "XYZ")
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gStyle.SetNdivisions(510, "XYZ")
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gStyle.SetPadTickX(1)
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gStyle.SetPadTickY(1)
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gROOT.ForceStyle()
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#set the text for the luminosity label
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if(intLumi < 1000.):
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LumiInPb = intLumi
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LumiText = "L_{int} = " + str(intLumi) + " pb^{-1}"
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LumiText = "L_{int} = " + str.format('{0:.1f}', LumiInPb) + " pb^{-1}"
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else:
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LumiInFb = intLumi/1000.
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LumiText = "L_{int} = " + str.format('{0:.1f}', LumiInFb) + " fb^{-1}"
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#bestest place for lumi. label, in top left corner
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topLeft_x_left = 0.1375839
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topLeft_x_right = 0.4580537
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topLeft_y_bottom = 0.8479021
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topLeft_y_top = 0.9475524
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topLeft_y_offset = 0.035
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#set the text for the fancy heading
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HeaderText = "CMS Preliminary: " + LumiText + " at #sqrt{s} = 8 TeV"
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#position for header
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header_x_left = 0.2181208
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header_x_right = 0.9562937
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header_y_bottom = 0.9479866
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header_y_top = 0.9947552
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##########################################################################################################################################
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##########################################################################################################################################
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##########################################################################################################################################
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# some fancy-ass code from Andrzej Zuranski to merge bins in the ratio plot until the error goes below some threshold
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def ratioHistogram( dataHist, mcHist, relErrMax=0.1):
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if not dataHist:
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print "Error: trying to run ratioHistogram but dataHist is invalid"
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return
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if not mcHist:
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print "Error: trying to run ratioHistogram but mcHist is invalid"
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return
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def groupR(group):
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Data,MC = [float(sum(hist.GetBinContent(i) for i in group)) for hist in [dataHist,mcHist]]
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return (Data-MC)/MC if MC else 0
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def groupErr(group):
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Data,MC = [float(sum(hist.GetBinContent(i) for i in group)) for hist in [dataHist,mcHist]]
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dataErr2,mcErr2 = [sum(hist.GetBinError(i)**2 for i in group) for hist in [dataHist,mcHist]]
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if Data > 0 and MC > 0 and Data != MC:
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return abs(math.sqrt( (dataErr2+mcErr2)/(Data-MC)**2 + mcErr2/MC**2 ) * (Data-MC)/MC)
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else:
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return 0
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def regroup(groups):
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err,iG = max( (groupErr(g),groups.index(g)) for g in groups )
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if err < relErrMax or len(groups)<3 : return groups
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iH = max( [iG-1,iG+1], key = lambda i: groupErr(groups[i]) if 0<=i<len(groups) else -1 )
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iLo,iHi = sorted([iG,iH])
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return regroup(groups[:iLo] + [groups[iLo]+groups[iHi]] + groups[iHi+1:])
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#don't rebin the histograms of the number of a given object (except for the pileup ones)
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if ((dataHist.GetName().find("num") is not -1 and dataHist.GetName().find("Primaryvertexs") is -1) or
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dataHist.GetName().find("CutFlow") is not -1 or
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dataHist.GetName().find("GenMatch") is not -1):
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ratio = dataHist.Clone()
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ratio.Add(mcHist,-1)
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ratio.Divide(mcHist)
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ratio.SetTitle("")
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else:
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groups = regroup( [(i,) for i in range(1,1+dataHist.GetNbinsX())] )
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ratio = TH1F("ratio","",len(groups), array('d', [dataHist.GetBinLowEdge(min(g)) for g in groups ] + [dataHist.GetXaxis().GetBinUpEdge(dataHist.GetNbinsX())]) )
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for i,g in enumerate(groups) :
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ratio.SetBinContent(i+1,groupR(g))
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ratio.SetBinError(i+1,groupErr(g))
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ratio.GetYaxis().SetTitle("#frac{Data-MC}{MC}")
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ratio.SetLineColor(1)
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ratio.SetLineWidth(2)
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return ratio
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##########################################################################################################################################
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##########################################################################################################################################
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##########################################################################################################################################
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def MakeOneDHist(pathToDir,histogramName):
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blindData = False
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# To blind histograms, define a list of histsToBlind in the localOptions.py file
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try: # Use "try" in case histsToBlind does not exist
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if histsToBlind:
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for histToBlind in histsToBlind:
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if histToBlind in histogramName:
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print "Blinding data for histogram " + histogramName
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blindData = True
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except NameError:
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time.sleep(0.000001) # Do nothing if histsToBlind does not exist
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numBgMCSamples = 0
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numDataSamples = 0
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numSignalSamples = 0
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Stack = THStack("stack",histogramName)
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HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
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HeaderLabel.SetTextAlign(32)
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HeaderLabel.SetBorderSize(0)
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HeaderLabel.SetFillColor(0)
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HeaderLabel.SetFillStyle(0)
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LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
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LumiLabel.SetBorderSize(0)
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LumiLabel.SetFillColor(0)
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LumiLabel.SetFillStyle(0)
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NormLabel = TPaveLabel()
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NormLabel.SetDrawOption("NDC")
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NormLabel.SetX1NDC(topLeft_x_left)
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NormLabel.SetX2NDC(topLeft_x_right)
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NormLabel.SetBorderSize(0)
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NormLabel.SetFillColor(0)
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NormLabel.SetFillStyle(0)
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NormText = ""
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if arguments.normalizeToUnitArea:
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NormText = "Scaled to unit area"
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elif arguments.normalizeToData:
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NormText = "MC scaled to data"
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NormLabel.SetLabel(NormText)
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BgMCLegend = TLegend()
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BgTitle = BgMCLegend.AddEntry(0, "Data & Bkgd. MC", "H")
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BgTitle.SetTextAlign(22)
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BgTitle.SetTextFont(62)
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BgMCLegend.SetBorderSize(0)
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BgMCLegend.SetFillColor(0)
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BgMCLegend.SetFillStyle(0)
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SignalMCLegend = TLegend()
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SignalTitle = SignalMCLegend.AddEntry(0, "Signal MC", "H")
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SignalTitle.SetTextAlign(22)
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SignalTitle.SetTextFont(62)
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SignalMCLegend.SetBorderSize(0)
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SignalMCLegend.SetFillColor(0)
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SignalMCLegend.SetFillStyle(0)
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outputFile.cd(pathToDir)
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Canvas = TCanvas(histogramName)
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BgMCHistograms = []
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BgMCLegendEntries = []
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SignalMCHistograms = []
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SignalMCLegendEntries = []
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DataHistograms = []
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DataLegendEntries = []
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backgroundIntegral = 0
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dataIntegral = 0
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scaleFactor = 1
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for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
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dataset_file = "%s/%s.root" % (condor_dir,sample)
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inputFile = TFile(dataset_file)
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HistogramObj = inputFile.Get(pathToDir+"/"+histogramName)
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if not HistogramObj:
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print "WARNING: Could not find histogram " + pathToDir + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
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continue
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Histogram = HistogramObj.Clone()
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Histogram.SetDirectory(0)
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inputFile.Close()
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if arguments.rebinFactor:
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RebinFactor = int(arguments.rebinFactor)
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#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
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if Histogram.GetNbinsX() >= RebinFactor*5 and Histogram.GetName().find("GenMatch") is -1:
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Histogram.Rebin(RebinFactor)
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xAxisLabel = Histogram.GetXaxis().GetTitle()
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unitBeginIndex = xAxisLabel.find("[")
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unitEndIndex = xAxisLabel.find("]")
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if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
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yAxisLabel = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(1)) + " " + xAxisLabel[unitBeginIndex+1:unitEndIndex]
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else:
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yAxisLabel = "Entries per bin (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
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if not arguments.makeFancy:
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histoTitle = Histogram.GetTitle()
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else:
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histoTitle = ""
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legLabel = labels[sample]
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if (arguments.printYields):
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yieldHist = Histogram.Integral()
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legLabel = legLabel + " (%.1f)" % yieldHist
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if( types[sample] == "bgMC"):
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numBgMCSamples += 1
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backgroundIntegral += Histogram.Integral()
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Histogram.SetLineStyle(1)
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if(arguments.noStack):
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Histogram.SetFillStyle(0)
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Histogram.SetLineColor(colors[sample])
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Histogram.SetLineWidth(2)
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else:
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Histogram.SetFillStyle(1001)
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Histogram.SetFillColor(colors[sample])
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Histogram.SetLineColor(1)
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Histogram.SetLineWidth(1)
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BgMCLegendEntries.append(legLabel)
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BgMCHistograms.append(Histogram)
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elif( types[sample] == "signalMC"):
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numSignalSamples += 1
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Histogram.SetFillStyle(0)
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Histogram.SetLineColor(colors[sample])
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Histogram.SetLineStyle(1)
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Histogram.SetLineWidth(2)
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if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
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Histogram.Scale(1./Histogram.Integral())
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SignalMCLegendEntries.append(legLabel)
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SignalMCHistograms.append(Histogram)
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elif( types[sample] == "data" and not blindData):
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numDataSamples += 1
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dataIntegral += Histogram.Integral()
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| 334 |
Histogram.SetMarkerStyle(20)
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Histogram.SetMarkerSize(0.8)
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| 336 |
Histogram.SetFillStyle(0)
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| 337 |
Histogram.SetLineColor(colors[sample])
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| 338 |
Histogram.SetLineStyle(1)
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| 339 |
Histogram.SetLineWidth(2)
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| 340 |
if(arguments.normalizeToUnitArea and Histogram.Integral() > 0):
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Histogram.Scale(1./Histogram.Integral())
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DataLegendEntries.append(legLabel)
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DataHistograms.append(Histogram)
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| 345 |
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| 346 |
#scaling histograms as per user's specifications
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| 347 |
if dataIntegral > 0 and backgroundIntegral > 0:
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scaleFactor = dataIntegral/backgroundIntegral
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| 349 |
for bgMCHist in BgMCHistograms:
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| 350 |
if arguments.normalizeToData:
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bgMCHist.Scale(scaleFactor)
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| 353 |
if arguments.normalizeToUnitArea and not arguments.noStack and backgroundIntegral > 0:
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bgMCHist.Scale(1./backgroundIntegral)
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| 355 |
elif arguments.normalizeToUnitArea and arguments.noStack and bgMCHist.Integral() > 0:
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bgMCHist.Scale(1./bgMCHist.Integral())
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| 357 |
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| 358 |
if not arguments.noStack:
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Stack.Add(bgMCHist)
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| 360 |
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| 361 |
|
| 362 |
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| 363 |
### formatting data histograms and adding to legend
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| 364 |
legendIndex = 0
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| 365 |
for Histogram in DataHistograms:
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| 366 |
BgMCLegend.AddEntry(Histogram,DataLegendEntries[legendIndex],"LEP")
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| 367 |
legendIndex = legendIndex+1
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| 368 |
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| 369 |
|
| 370 |
### creating the histogram to represent the statistical errors on the stack
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| 371 |
if numBgMCSamples is not 0 and not arguments.noStack:
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| 372 |
ErrorHisto = BgMCHistograms[0].Clone("errors")
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| 373 |
ErrorHisto.SetFillStyle(3001)
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| 374 |
ErrorHisto.SetFillColor(13)
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| 375 |
ErrorHisto.SetLineWidth(0)
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| 376 |
BgMCLegend.AddEntry(ErrorHisto,"Stat. Errors","F")
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| 377 |
for Histogram in BgMCHistograms:
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| 378 |
if Histogram is not BgMCHistograms[0]:
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ErrorHisto.Add(Histogram)
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| 381 |
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| 382 |
### formatting bgMC histograms and adding to legend
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| 383 |
legendIndex = numBgMCSamples-1
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| 384 |
for Histogram in reversed(BgMCHistograms):
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| 385 |
if(arguments.noStack):
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| 386 |
BgMCLegend.AddEntry(Histogram,BgMCLegendEntries[legendIndex],"L")
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| 387 |
else:
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| 388 |
BgMCLegend.AddEntry(Histogram,BgMCLegendEntries[legendIndex],"F")
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| 389 |
legendIndex = legendIndex-1
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| 390 |
|
| 391 |
|
| 392 |
### formatting signalMC histograms and adding to legend
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| 393 |
legendIndex = 0
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| 394 |
for Histogram in SignalMCHistograms:
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| 395 |
SignalMCLegend.AddEntry(Histogram,SignalMCLegendEntries[legendIndex],"L")
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| 396 |
legendIndex = legendIndex+1
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| 397 |
|
| 398 |
|
| 399 |
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
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| 400 |
finalMax = 0
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| 401 |
if numBgMCSamples is not 0 and not arguments.noStack:
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| 402 |
finalMax = ErrorHisto.GetMaximum() + ErrorHisto.GetBinError(ErrorHisto.GetMaximumBin())
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| 403 |
else:
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| 404 |
for bgMCHist in BgMCHistograms:
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| 405 |
if(bgMCHist.GetMaximum() > finalMax):
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| 406 |
finalMax = bgMCHist.GetMaximum()
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| 407 |
for signalMCHist in SignalMCHistograms:
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| 408 |
if(signalMCHist.GetMaximum() > finalMax):
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| 409 |
finalMax = signalMCHist.GetMaximum()
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| 410 |
for dataHist in DataHistograms:
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| 411 |
if(dataHist.GetMaximum() > finalMax):
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| 412 |
finalMax = dataHist.GetMaximum() + dataHist.GetBinError(dataHist.GetMaximumBin())
|
| 413 |
finalMax = 1.15*finalMax
|
| 414 |
if arguments.setYMax:
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| 415 |
finalMax = float(arguments.setYMax)
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| 416 |
|
| 417 |
|
| 418 |
### Drawing histograms to canvas
|
| 419 |
|
| 420 |
outputFile.cd(pathToDir)
|
| 421 |
|
| 422 |
makeRatioPlots = arguments.makeRatioPlots
|
| 423 |
makeDiffPlots = arguments.makeDiffPlots
|
| 424 |
|
| 425 |
yAxisMin = 0.0001
|
| 426 |
if arguments.setYMin:
|
| 427 |
yAxisMin = float(arguments.setYMin)
|
| 428 |
|
| 429 |
if numBgMCSamples is 0 or numDataSamples is not 1:
|
| 430 |
makeRatioPlots = False
|
| 431 |
makeDiffPlots = False
|
| 432 |
if makeRatioPlots or makeDiffPlots:
|
| 433 |
Canvas.SetFillStyle(0)
|
| 434 |
Canvas.Divide(1,2)
|
| 435 |
Canvas.cd(1)
|
| 436 |
gPad.SetPad(0,0.25,1,1)
|
| 437 |
gPad.SetMargin(0.15,0.05,0.01,0.07)
|
| 438 |
gPad.SetFillStyle(0)
|
| 439 |
gPad.Update()
|
| 440 |
gPad.Draw()
|
| 441 |
if arguments.setLogY:
|
| 442 |
gPad.SetLogy()
|
| 443 |
Canvas.cd(2)
|
| 444 |
gPad.SetPad(0,0,1,0.25)
|
| 445 |
#format: gPad.SetMargin(l,r,b,t)
|
| 446 |
gPad.SetMargin(0.15,0.05,0.4,0.01)
|
| 447 |
gPad.SetFillStyle(0)
|
| 448 |
gPad.SetGridy(1)
|
| 449 |
gPad.Update()
|
| 450 |
gPad.Draw()
|
| 451 |
|
| 452 |
Canvas.cd(1)
|
| 453 |
|
| 454 |
if numBgMCSamples is not 0: # the first thing to draw to the canvas is a bgMC sample
|
| 455 |
|
| 456 |
if not arguments.noStack: # draw stacked background samples
|
| 457 |
Stack.SetTitle(histoTitle)
|
| 458 |
Stack.Draw("HIST")
|
| 459 |
Stack.GetXaxis().SetTitle(xAxisLabel)
|
| 460 |
Stack.GetYaxis().SetTitle(yAxisLabel)
|
| 461 |
Stack.SetMaximum(finalMax)
|
| 462 |
Stack.SetMinimum(yAxisMin)
|
| 463 |
if makeRatioPlots or makeDiffPlots:
|
| 464 |
Stack.GetHistogram().GetXaxis().SetLabelSize(0)
|
| 465 |
#draw shaded error bands
|
| 466 |
ErrorHisto.Draw("A E2 SAME")
|
| 467 |
|
| 468 |
else: #draw the unstacked backgrounds
|
| 469 |
BgMCHistograms[0].SetTitle(histoTitle)
|
| 470 |
BgMCHistograms[0].Draw("HIST")
|
| 471 |
BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
|
| 472 |
BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
|
| 473 |
BgMCHistograms[0].SetMaximum(finalMax)
|
| 474 |
BgMCHistograms[0].SetMinimum(yAxisMin)
|
| 475 |
for bgMCHist in BgMCHistograms:
|
| 476 |
bgMCHist.Draw("A HIST SAME")
|
| 477 |
|
| 478 |
for signalMCHist in SignalMCHistograms:
|
| 479 |
signalMCHist.Draw("A HIST SAME")
|
| 480 |
for dataHist in DataHistograms:
|
| 481 |
dataHist.Draw("A E X0 SAME")
|
| 482 |
|
| 483 |
|
| 484 |
elif numSignalSamples is not 0: # the first thing to draw to the canvas is a signalMC sample
|
| 485 |
SignalMCHistograms[0].SetTitle(histoTitle)
|
| 486 |
SignalMCHistograms[0].Draw("HIST")
|
| 487 |
SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
|
| 488 |
SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
|
| 489 |
SignalMCHistograms[0].SetMaximum(finalMax)
|
| 490 |
SignalMCHistograms[0].SetMinimum(yAxisMin)
|
| 491 |
|
| 492 |
for signalMCHist in SignalMCHistograms:
|
| 493 |
if(signalMCHist is not SignalMCHistograms[0]):
|
| 494 |
signalMCHist.Draw("A HIST SAME")
|
| 495 |
for dataHist in DataHistograms:
|
| 496 |
dataHist.Draw("A E X0 SAME")
|
| 497 |
|
| 498 |
|
| 499 |
elif(numDataSamples is not 0): # the first thing to draw to the canvas is a data sample
|
| 500 |
DataHistograms[0].SetTitle(histoTitle)
|
| 501 |
DataHistograms[0].Draw("E")
|
| 502 |
DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
|
| 503 |
DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
|
| 504 |
DataHistograms[0].SetMaximum(finalMax)
|
| 505 |
DataHistograms[0].SetMinimum(yAxisMin)
|
| 506 |
for dataHist in DataHistograms:
|
| 507 |
if(dataHist is not DataHistograms[0]):
|
| 508 |
dataHist.Draw("A E X0 SAME")
|
| 509 |
|
| 510 |
|
| 511 |
|
| 512 |
#legend coordinates, empirically determined :-)
|
| 513 |
x_left = 0.6761745
|
| 514 |
x_right = 0.9328859
|
| 515 |
x_width = x_right - x_left
|
| 516 |
y_max = 0.9
|
| 517 |
entry_height = 0.05
|
| 518 |
|
| 519 |
if(numBgMCSamples is not 0 or numDataSamples is not 0): #then draw the data & bgMC legend
|
| 520 |
|
| 521 |
numExtraEntries = 1 # count the legend title
|
| 522 |
BgMCLegend.SetX1NDC(x_left)
|
| 523 |
if numBgMCSamples > 0:
|
| 524 |
numExtraEntries = numExtraEntries + 1 # count the stat. errors entry
|
| 525 |
|
| 526 |
BgMCLegend.SetY1NDC(y_max-entry_height*(numExtraEntries+numBgMCSamples+numDataSamples))
|
| 527 |
BgMCLegend.SetX2NDC(x_right)
|
| 528 |
BgMCLegend.SetY2NDC(y_max)
|
| 529 |
BgMCLegend.Draw()
|
| 530 |
|
| 531 |
if(numSignalSamples is not 0): #then draw the signalMC legend to the left of the other one
|
| 532 |
SignalMCLegend.SetX1NDC(x_left-x_width)
|
| 533 |
SignalMCLegend.SetY1NDC(y_max-entry_height*(1+numSignalSamples)) # add one for the title
|
| 534 |
SignalMCLegend.SetX2NDC(x_left)
|
| 535 |
SignalMCLegend.SetY2NDC(y_max)
|
| 536 |
SignalMCLegend.Draw()
|
| 537 |
|
| 538 |
elif numSignalSamples is not 0: #draw the signalMC legend in the upper right corner
|
| 539 |
SignalMCLegend.SetX1NDC(x_left)
|
| 540 |
SignalMCLegend.SetY1NDC(y_max-entry_height*(1+numSignalSamples)) # add one for the title
|
| 541 |
SignalMCLegend.SetX2NDC(x_right)
|
| 542 |
SignalMCLegend.SetY2NDC(y_max)
|
| 543 |
SignalMCLegend.Draw()
|
| 544 |
|
| 545 |
|
| 546 |
# Deciding which text labels to draw and drawing them
|
| 547 |
drawLumiLabel = False
|
| 548 |
drawNormLabel = False
|
| 549 |
offsetNormLabel = False
|
| 550 |
drawHeaderLabel = False
|
| 551 |
|
| 552 |
if not arguments.normalizeToUnitArea or numDataSamples > 0: #don't draw the lumi label if there's no data and it's scaled to unit area
|
| 553 |
drawLumiLabel = True
|
| 554 |
#move the normalization label down before drawing if we drew the lumi. label
|
| 555 |
offsetNormLabel = True
|
| 556 |
if arguments.normalizeToUnitArea or arguments.normalizeToData:
|
| 557 |
drawNormLabel = True
|
| 558 |
if arguments.makeFancy:
|
| 559 |
drawHeaderLabel = True
|
| 560 |
drawLumiLabel = False
|
| 561 |
|
| 562 |
#now that flags are set, draw the appropriate labels
|
| 563 |
|
| 564 |
if drawLumiLabel:
|
| 565 |
LumiLabel.Draw()
|
| 566 |
|
| 567 |
if drawNormLabel:
|
| 568 |
if offsetNormLabel:
|
| 569 |
NormLabel.SetY1NDC(topLeft_y_bottom-topLeft_y_offset)
|
| 570 |
NormLabel.SetY2NDC(topLeft_y_top-topLeft_y_offset)
|
| 571 |
else:
|
| 572 |
NormLabel.SetY1NDC(topLeft_y_bottom)
|
| 573 |
NormLabel.SetY2NDC(topLeft_y_top)
|
| 574 |
NormLabel.Draw()
|
| 575 |
|
| 576 |
if drawHeaderLabel:
|
| 577 |
HeaderLabel.Draw()
|
| 578 |
|
| 579 |
|
| 580 |
|
| 581 |
|
| 582 |
#drawing the ratio or difference plot if requested
|
| 583 |
|
| 584 |
if (makeRatioPlots or makeDiffPlots):
|
| 585 |
Canvas.cd(2)
|
| 586 |
BgSum = Stack.GetStack().Last()
|
| 587 |
if makeRatioPlots:
|
| 588 |
if arguments.ratioRelErrMax:
|
| 589 |
Comparison = ratioHistogram(DataHistograms[0],BgSum,arguments.ratioRelErrMax)
|
| 590 |
else:
|
| 591 |
Comparison = ratioHistogram(DataHistograms[0],BgSum)
|
| 592 |
elif makeDiffPlots:
|
| 593 |
Comparison = DataHistograms[0].Clone("diff")
|
| 594 |
Comparison.Add(BgSum,-1)
|
| 595 |
Comparison.SetTitle("")
|
| 596 |
Comparison.GetYaxis().SetTitle("Data-MC")
|
| 597 |
Comparison.GetXaxis().SetTitle(xAxisLabel)
|
| 598 |
Comparison.GetYaxis().CenterTitle()
|
| 599 |
Comparison.GetYaxis().SetTitleSize(0.1)
|
| 600 |
Comparison.GetYaxis().SetTitleOffset(0.5)
|
| 601 |
Comparison.GetXaxis().SetTitleSize(0.15)
|
| 602 |
Comparison.GetYaxis().SetLabelSize(0.1)
|
| 603 |
Comparison.GetXaxis().SetLabelSize(0.15)
|
| 604 |
if makeRatioPlots:
|
| 605 |
RatioYRange = 1.15
|
| 606 |
if arguments.ratioYRange:
|
| 607 |
RatioYRange = float(arguments.ratioYRange)
|
| 608 |
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
|
| 609 |
elif makeDiffPlots:
|
| 610 |
YMax = Comparison.GetMaximum()
|
| 611 |
YMin = Comparison.GetMinimum()
|
| 612 |
if YMax <= 0 and YMin <= 0:
|
| 613 |
Comparison.GetYaxis().SetRangeUser(-1.2*YMin,0)
|
| 614 |
elif YMax >= 0 and YMin >= 0:
|
| 615 |
Comparison.GetYaxis().SetRangeUser(0,1.2*YMax)
|
| 616 |
else: #axis crosses y=0
|
| 617 |
if abs(YMax) > abs(YMin):
|
| 618 |
Comparison.GetYaxis().SetRangeUser(-1.2*YMax,1.2*YMax)
|
| 619 |
else:
|
| 620 |
Comparison.GetYaxis().SetRangeUser(-1.2*YMin,1.2*YMin)
|
| 621 |
|
| 622 |
Comparison.GetYaxis().SetNdivisions(205)
|
| 623 |
Comparison.Draw()
|
| 624 |
|
| 625 |
Canvas.Write()
|
| 626 |
if arguments.savePDFs:
|
| 627 |
pathToDirString = plainTextString(pathToDir)
|
| 628 |
Canvas.SaveAs(condor_dir+"/stacked_histograms_pdfs/"+pathToDirString+"/"+histogramName+".pdf")
|
| 629 |
|
| 630 |
|
| 631 |
##########################################################################################################################################
|
| 632 |
##########################################################################################################################################
|
| 633 |
##########################################################################################################################################
|
| 634 |
|
| 635 |
def MakeTwoDHist(pathToDir,histogramName):
|
| 636 |
blindData = False
|
| 637 |
# To blind histograms, define a list of histsToBlind in the localOptions.py file
|
| 638 |
try: # Use "try" in case histsToBlind does not exist
|
| 639 |
if histsToBlind:
|
| 640 |
for histToBlind in histsToBlind:
|
| 641 |
if histToBlind in histogramName:
|
| 642 |
print "Blinding data for histogram " + histogramName
|
| 643 |
blindData = True
|
| 644 |
except NameError:
|
| 645 |
time.sleep(0.000001) # Do nothing if histsToBlind does not exist
|
| 646 |
|
| 647 |
numBgMCSamples = 0
|
| 648 |
numDataSamples = 0
|
| 649 |
numSignalSamples = 0
|
| 650 |
|
| 651 |
|
| 652 |
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
|
| 653 |
HeaderLabel.SetTextAlign(32)
|
| 654 |
HeaderLabel.SetBorderSize(0)
|
| 655 |
HeaderLabel.SetFillColor(0)
|
| 656 |
HeaderLabel.SetFillStyle(0)
|
| 657 |
|
| 658 |
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
|
| 659 |
LumiLabel.SetBorderSize(0)
|
| 660 |
LumiLabel.SetFillColor(0)
|
| 661 |
LumiLabel.SetFillStyle(0)
|
| 662 |
|
| 663 |
NormLabel = TPaveLabel()
|
| 664 |
NormLabel.SetDrawOption("NDC")
|
| 665 |
NormLabel.SetX1NDC(topLeft_x_left)
|
| 666 |
NormLabel.SetX2NDC(topLeft_x_right)
|
| 667 |
|
| 668 |
NormLabel.SetBorderSize(0)
|
| 669 |
NormLabel.SetFillColor(0)
|
| 670 |
NormLabel.SetFillStyle(0)
|
| 671 |
|
| 672 |
NormText = ""
|
| 673 |
if arguments.normalizeToUnitArea:
|
| 674 |
NormText = "Scaled to unit area"
|
| 675 |
elif arguments.normalizeToData:
|
| 676 |
NormText = "MC scaled to data"
|
| 677 |
NormLabel.SetLabel(NormText)
|
| 678 |
|
| 679 |
BgMCLegend = TLegend(0.76,0.65,0.99,0.9)
|
| 680 |
BgMCLegend.AddEntry (0, "Data & Bkgd. MC", "H").SetTextFont (62)
|
| 681 |
BgMCLegend.SetBorderSize(0)
|
| 682 |
BgMCLegend.SetFillColor(0)
|
| 683 |
BgMCLegend.SetFillStyle(0)
|
| 684 |
SignalMCLegend = TLegend(0.76,0.135,0.99,0.377)
|
| 685 |
SignalMCLegend.AddEntry (0, "Signal MC", "H").SetTextFont (62)
|
| 686 |
SignalMCLegend.SetBorderSize(0)
|
| 687 |
SignalMCLegend.SetFillColor(0)
|
| 688 |
SignalMCLegend.SetFillStyle(0)
|
| 689 |
|
| 690 |
outputFile.cd(pathToDir)
|
| 691 |
Canvas = TCanvas(histogramName)
|
| 692 |
Canvas.SetRightMargin(0.2413793);
|
| 693 |
BgMCHistograms = []
|
| 694 |
SignalMCHistograms = []
|
| 695 |
DataHistograms = []
|
| 696 |
|
| 697 |
for sample in processed_datasets: # loop over different samples as listed in configurationOptions.py
|
| 698 |
dataset_file = "%s/%s.root" % (condor_dir,sample)
|
| 699 |
inputFile = TFile(dataset_file)
|
| 700 |
HistogramObj = inputFile.Get(pathToDir+"/"+histogramName)
|
| 701 |
if not HistogramObj:
|
| 702 |
print "WARNING: Could not find histogram " + pathToDir + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
|
| 703 |
continue
|
| 704 |
Histogram = HistogramObj.Clone()
|
| 705 |
Histogram.SetDirectory(0)
|
| 706 |
inputFile.Close()
|
| 707 |
if arguments.rebinFactor:
|
| 708 |
RebinFactor = int(arguments.rebinFactor)
|
| 709 |
#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
|
| 710 |
if Histogram.GetNbinsX() >= RebinFactor*5 and Histogram.GetName().find("GenMatch") is -1:
|
| 711 |
Histogram.Rebin(RebinFactor)
|
| 712 |
xAxisLabel = Histogram.GetXaxis().GetTitle()
|
| 713 |
yAxisLabel = Histogram.GetYaxis().GetTitle()
|
| 714 |
if not arguments.makeFancy:
|
| 715 |
histoTitle = Histogram.GetTitle()
|
| 716 |
else:
|
| 717 |
histoTitle = ""
|
| 718 |
|
| 719 |
if( types[sample] == "bgMC"):
|
| 720 |
|
| 721 |
numBgMCSamples += 1
|
| 722 |
Histogram.SetMarkerColor(colors[sample])
|
| 723 |
Histogram.SetMarkerStyle(24)
|
| 724 |
Histogram.SetMarkerSize(1.2)
|
| 725 |
Histogram.SetFillColor(colors[sample])
|
| 726 |
BgMCLegend.AddEntry(Histogram,labels[sample],"P").SetTextFont (42)
|
| 727 |
BgMCHistograms.append(Histogram)
|
| 728 |
|
| 729 |
elif( types[sample] == "signalMC"):
|
| 730 |
|
| 731 |
numSignalSamples += 1
|
| 732 |
Histogram.SetMarkerColor(colors[sample])
|
| 733 |
Histogram.SetMarkerStyle(20)
|
| 734 |
Histogram.SetMarkerSize(1.2)
|
| 735 |
Histogram.SetFillColor(colors[sample])
|
| 736 |
BgMCLegend.AddEntry(Histogram,labels[sample],"P").SetTextFont (42)
|
| 737 |
# SignalMCLegend.AddEntry(Histogram,labels[sample],"P").SetTextFont (42)
|
| 738 |
SignalMCHistograms.append(Histogram)
|
| 739 |
|
| 740 |
elif( types[sample] == "data" and not blindData):
|
| 741 |
|
| 742 |
numDataSamples += 1
|
| 743 |
Histogram.SetMarkerColor(colors[sample])
|
| 744 |
Histogram.SetMarkerStyle(34)
|
| 745 |
Histogram.SetMarkerSize(1.2)
|
| 746 |
Histogram.SetFillColor(colors[sample])
|
| 747 |
BgMCLegend.AddEntry(Histogram,labels[sample],"P").SetTextFont (42)
|
| 748 |
DataHistograms.append(Histogram)
|
| 749 |
|
| 750 |
|
| 751 |
outputFile.cd(pathToDir)
|
| 752 |
|
| 753 |
if(numBgMCSamples is not 0):
|
| 754 |
BgMCHistograms[0].SetTitle(histoTitle)
|
| 755 |
BgMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
|
| 756 |
BgMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
|
| 757 |
BgMCHistograms[0].Draw()
|
| 758 |
for signalMCHist in SignalMCHistograms:
|
| 759 |
signalMCHist.Draw("SAME")
|
| 760 |
for dataHist in DataHistograms:
|
| 761 |
dataHist.Draw("SAME")
|
| 762 |
|
| 763 |
elif(numSignalSamples is not 0):
|
| 764 |
SignalMCHistograms[0].SetTitle(histoTitle)
|
| 765 |
SignalMCHistograms[0].Draw()
|
| 766 |
SignalMCHistograms[0].GetXaxis().SetTitle(xAxisLabel)
|
| 767 |
SignalMCHistograms[0].GetYaxis().SetTitle(yAxisLabel)
|
| 768 |
for signalMCHist in SignalMCHistograms:
|
| 769 |
if(signalMCHist is not SignalMCHistograms[0]):
|
| 770 |
signalMCHist.Draw("SAME")
|
| 771 |
for dataHist in DataHistograms:
|
| 772 |
dataHist.Draw("SAME")
|
| 773 |
|
| 774 |
elif(numDataSamples is not 0):
|
| 775 |
DataHistograms[0].SetTitle(histoTitle)
|
| 776 |
DataHistograms[0].GetXaxis().SetTitle(xAxisLabel)
|
| 777 |
DataHistograms[0].GetYaxis().SetTitle(yAxisLabel)
|
| 778 |
DataHistograms[0].Draw()
|
| 779 |
for dataHist in DataHistograms:
|
| 780 |
if(dataHist is not DataHistograms[0]):
|
| 781 |
dataHist.Draw("SAME")
|
| 782 |
|
| 783 |
|
| 784 |
|
| 785 |
# Deciding which text labels to draw and drawing them
|
| 786 |
drawLumiLabel = False
|
| 787 |
drawNormLabel = False
|
| 788 |
offsetNormLabel = False
|
| 789 |
drawHeaderLabel = False
|
| 790 |
|
| 791 |
if not arguments.normalizeToUnitArea or numDataSamples > 0: #don't draw the lumi label if there's no data and it's scaled to unit area
|
| 792 |
drawLumiLabel = True
|
| 793 |
#move the normalization label down before drawing if we drew the lumi. label
|
| 794 |
offsetNormLabel = True
|
| 795 |
if arguments.normalizeToUnitArea or arguments.normalizeToData:
|
| 796 |
drawNormLabel = True
|
| 797 |
if arguments.makeFancy:
|
| 798 |
drawHeaderLabel = True
|
| 799 |
drawLumiLabel = False
|
| 800 |
|
| 801 |
#now that flags are set, draw the appropriate labels
|
| 802 |
|
| 803 |
if drawLumiLabel:
|
| 804 |
LumiLabel.Draw()
|
| 805 |
|
| 806 |
if drawNormLabel:
|
| 807 |
if offsetNormLabel:
|
| 808 |
NormLabel.SetY1NDC(topLeft_y_bottom-topLeft_y_offset)
|
| 809 |
NormLabel.SetY2NDC(topLeft_y_top-topLeft_y_offset)
|
| 810 |
else:
|
| 811 |
NormLabel.SetY1NDC(topLeft_y_bottom)
|
| 812 |
NormLabel.SetY2NDC(topLeft_y_top)
|
| 813 |
NormLabel.Draw()
|
| 814 |
|
| 815 |
if drawHeaderLabel:
|
| 816 |
HeaderLabel.Draw()
|
| 817 |
|
| 818 |
|
| 819 |
|
| 820 |
|
| 821 |
if(numBgMCSamples is not 0 or numDataSamples is not 0):
|
| 822 |
BgMCLegend.Draw()
|
| 823 |
if(numSignalSamples is not 0):
|
| 824 |
SignalMCLegend.Draw()
|
| 825 |
|
| 826 |
Canvas.Write()
|
| 827 |
|
| 828 |
|
| 829 |
|
| 830 |
|
| 831 |
##########################################################################################################################################
|
| 832 |
##########################################################################################################################################
|
| 833 |
##########################################################################################################################################
|
| 834 |
|
| 835 |
processed_datasets = []
|
| 836 |
|
| 837 |
condor_dir = set_condor_output_dir(arguments)
|
| 838 |
|
| 839 |
#### check which input datasets have valid output files
|
| 840 |
for sample in datasets:
|
| 841 |
fileName = condor_dir + "/" + sample + ".root"
|
| 842 |
if not os.path.exists(fileName):
|
| 843 |
continue
|
| 844 |
testFile = TFile(fileName)
|
| 845 |
if testFile.IsZombie() or not testFile.GetNkeys():
|
| 846 |
continue
|
| 847 |
processed_datasets.append(sample)
|
| 848 |
|
| 849 |
if len(processed_datasets) is 0:
|
| 850 |
sys.exit("No datasets have been processed")
|
| 851 |
|
| 852 |
|
| 853 |
#### make output file
|
| 854 |
outputFileName = "stacked_histograms.root"
|
| 855 |
if arguments.outputFileName:
|
| 856 |
outputFileName = arguments.outputFileName
|
| 857 |
|
| 858 |
outputFile = TFile(condor_dir + "/" + outputFileName, "RECREATE")
|
| 859 |
|
| 860 |
|
| 861 |
|
| 862 |
#### use the first input file as a template and make stacked versions of all its histograms
|
| 863 |
inputFile = TFile(condor_dir + "/" + processed_datasets[0] + ".root")
|
| 864 |
inputFile.cd()
|
| 865 |
outputFile.cd()
|
| 866 |
|
| 867 |
if arguments.savePDFs:
|
| 868 |
os.system("rm -rf %s/stacked_histograms_pdfs" % (condor_dir))
|
| 869 |
os.system("mkdir %s/stacked_histograms_pdfs" % (condor_dir))
|
| 870 |
|
| 871 |
|
| 872 |
#get root directory in the first layer, generally "OSUAnalysis"
|
| 873 |
for key in inputFile.GetListOfKeys():
|
| 874 |
if (key.GetClassName() != "TDirectoryFile"):
|
| 875 |
continue
|
| 876 |
rootDirectory = key.GetName()
|
| 877 |
outputFile.mkdir(rootDirectory)
|
| 878 |
if arguments.savePDFs:
|
| 879 |
os.system("mkdir %s/stacked_histograms_pdfs/%s" % (condor_dir,plainTextString(rootDirectory)))
|
| 880 |
|
| 881 |
#cd to root directory and look for histograms
|
| 882 |
inputFile.cd(rootDirectory)
|
| 883 |
for key2 in gDirectory.GetListOfKeys():
|
| 884 |
|
| 885 |
if re.match ('TH1', key2.GetClassName()): # found a 1-D histogram
|
| 886 |
MakeOneDHist(rootDirectory,key2.GetName())
|
| 887 |
elif re.match ('TH2', key2.GetClassName()) and arguments.draw2DPlots: # found a 2-D histogram
|
| 888 |
MakeTwoDHist(rootDirectory,key2.GetName())
|
| 889 |
|
| 890 |
elif (key2.GetClassName() == "TDirectoryFile"): # found a directory, cd there and look for histograms
|
| 891 |
level2Directory = rootDirectory+"/"+key2.GetName()
|
| 892 |
|
| 893 |
#make a corresponding directory in the output file
|
| 894 |
outputFile.cd(rootDirectory)
|
| 895 |
gDirectory.mkdir(key2.GetName())
|
| 896 |
if arguments.savePDFs:
|
| 897 |
os.system("mkdir %s/stacked_histograms_pdfs/%s" % (condor_dir,plainTextString(level2Directory)))
|
| 898 |
|
| 899 |
#####################################################
|
| 900 |
### This layer is typically the "channels" layer ###
|
| 901 |
#####################################################
|
| 902 |
|
| 903 |
inputFile.cd(level2Directory)
|
| 904 |
for key3 in gDirectory.GetListOfKeys():
|
| 905 |
if re.match ('TH1', key3.GetClassName()): # found a 1-D histogram
|
| 906 |
MakeOneDHist(level2Directory,key3.GetName())
|
| 907 |
elif re.match ('TH2', key3.GetClassName()) and arguments.draw2DPlots: # found a 2-D histogram
|
| 908 |
MakeTwoDHist(level2Directory,key3.GetName())
|
| 909 |
|
| 910 |
elif (key3.GetClassName() == "TDirectoryFile"): # found a directory, cd there and look for histograms
|
| 911 |
level3Directory = level2Directory+"/"+key3.GetName()
|
| 912 |
|
| 913 |
#make a corresponding directory in the output file
|
| 914 |
outputFile.cd(level2Directory)
|
| 915 |
gDirectory.mkdir(key3.GetName())
|
| 916 |
if arguments.savePDFs:
|
| 917 |
os.system("mkdir %s/stacked_histograms_pdfs/%s" % (condor_dir,plainTextString(level3Directory)))
|
| 918 |
|
| 919 |
#################################################
|
| 920 |
### This layer is typically the "cuts" layer ###
|
| 921 |
#################################################
|
| 922 |
|
| 923 |
inputFile.cd(level3Directory)
|
| 924 |
for key3 in gDirectory.GetListOfKeys():
|
| 925 |
if re.match ('TH1', key3.GetClassName()): # found a 1-D histogram
|
| 926 |
MakeOneDHist(level3Directory,key3.GetName())
|
| 927 |
elif re.match ('TH2', key3.GetClassName()) and arguments.draw2DPlots: # found a 2-D histogram
|
| 928 |
MakeTwoDHist(level3Directory,key3.GetName())
|
| 929 |
|
| 930 |
|
| 931 |
outputFile.Close()
|
